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Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference

by Heena Kapila, Satwinder Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 2
Year of Publication: 2013
Authors: Heena Kapila, Satwinder Singh
10.5120/12854-9152

Heena Kapila, Satwinder Singh . Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference. International Journal of Computer Applications. 74, 2 ( July 2013), 1-4. DOI=10.5120/12854-9152

@article{ 10.5120/12854-9152,
author = { Heena Kapila, Satwinder Singh },
title = { Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 2 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number2/12854-9152/ },
doi = { 10.5120/12854-9152 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:08.046544+05:30
%A Heena Kapila
%A Satwinder Singh
%T Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 2
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The fault prediction model grants assistance during the software development by providing recourse to the present faults with the Bayesian Interference. All faults prediction techniques get a help in this study with the designing of Logistic regression model and Bayesian inference altogether. It is also told as fact that Bayesian inference graph can be represented for probabilistic approach for the faults both presented and identified for the upcoming release. For Probabilistic reliability analysis, Bayesian inference is intended to be evaluated for risk related data. These findings suggest that there is a relationship between faulty classes and object-oriented metrics. This study demonstrates as the performance evaluation technique for any piece of software. We examine the open source Eclipse system, which has a strong industrial usage. The focus of the study is to design Bayesian Inference graph and predict faults for next piece of software.

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Index Terms

Computer Science
Information Sciences

Keywords

Bayesian Inference Fault Prediction Software reliability CK metrics

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